01. Churn Rates Calculation

Project Goals

Four months into launching Codeflix, management asks to look into subscription churn rates. It’s early on in the business and people are excited to know how the company is doing. The marketing department is particularly interested in how the churn compares between two segments of users. They provide a dataset containing subscription data for users who were acquired through two distinct channels. Codeflix requires a minimum subscription length of 31 days, so a user can never start and end their subscription in the same month.

• Calculation of the churn rates for the two segments over the three month period. Which segment has a lower churn rate?

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02. Marketing Click Through Rate Analytics

Project Goals

CoolTShirts sells shirts of all kinds, as long as they are T-shaped and cool. Recently, CTS started a few marketing campaigns to increase website visits and purchases. Using touch attribution, they’d like to map their customers’ journey: from initial visit to purchase. They can use that information to optimize their marketing campaigns.I tried to answer following questions with sql query.

• How many campaigns and sources does CoolTShirts use? Which source is used for each campaign?
• What pages are on the CoolTShirts website?
• How many first touches is each campaign responsible for?
• How many last touches is each campaign responsible for?
• How many visitors make a purchase?
• How many last touches on the purchase page is each campaign responsible for?
• CoolTShirts can re-invest in 5 campaigns. Given your findings in the project, which should they pick and why?

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03. World Populations II

Project Goals

Here I worked on a dataset of world population by country data from recent years. Tried to write queries to retrieve interesting data and answer a set of specific questions.

• How many entries in the countries table are from Africa?
• What was the total population of the continent of Oceania in 2005?
• What is the average population of countries in South America in 2003?
• What country had the smallest population in 2007?
• What is the average population of Poland during the time period covered by this dataset?
• How many countries have the word “The” in their name?
• What was the total population of each continent in 2010?

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04. Trends in Startups

Project Goals

The task was to write an article on the rising trends in the startup world. To get started with the research, I started with a project.sqlite file that contains a table called startups. It is a portfolio of some of the biggest names in the industry. Data collected from TechCrunch.

• Calculating total number of companies in the table.
• We want to know the total value of all companies in this table.
• What is the highest amount raised by a startup at ‘Seed’ Stage?
• In what year was the oldest company on the list founded?
• Let’s find out the valuations among different sectors:
  • Average valuation, in each category.
• What are the most competitive markets?
  • What are the most competitive markets?
• Let’s see if there’s a difference in startups sizes among different locations:
  • What is the average size of a startup in each location, with average sizes above 500?

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05. World Populations SQL I

Project Goals

Here is a dataset of world population by country data from recent years. I tried to answer following questions with sql query.

• What years are covered by the dataset?
• What is the largest population size for Gabon in this dataset?
• What were the 10 lowest population countries in 2005?
• What are all the distinct countries with a population of over 100 million in the year 2010?
• How many countries in this dataset have the word “Islands” in their name?
• What is the difference in population between 2000 and 2010 in Indonesia?

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06. RPA Fraud Detection

Project Goals

Reputable Product Agency (RPA) has started receiving complaints from their credit card processor about fraudulent transactions. I tried to answer following assumptions with sql query.

• The finance department noted that some of the fraudulent transactions were recorded as coming from Smokey Bear’s zip code (20252).
• Finance has also noticed a number of pseudonyms associated with fraudulent transactions. The fraudsters thought it would be funny to use ‘Art Vandelay’ for their full name or add a ‘der’ for their middle name.
• There are some irregularities in the IP addresses where transactions are originating from. For example, any IP address beginning with ‘10.’ is reserved for internal use.
• Users are making fraudulent transactions using a temporary email address service. These services provide a short-lived email that can be verified and then self-destructs.
• The finance department is looking for a specific transaction. They know that the transaction occurred from an ip address starting with ‘120.’ and their full name starts with ‘John’.

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07. RPA Customer Segmentation

Project Goals

The marketing department of Reputable Product Agency (RPA) is looking to segment the company users by a number of different criteria. In this context, a segment is a subset of users that meet different conditions. Segments are used to send marketing campaigns to users who meet specific criteria or to measure the performance of specific marketing campaigns. I tried to retrieve data under following circumstances with sql query.

• The marketing department wants to send a Born in the ‘80s email to the appropriate users.

• We are interested in the cohort of users that signed up prior to May 2017.

• There was an A/B test performed on users that used cute animal clipart to encourage users to sign up. We’d like to see how the group that was shown ‘bears’ is performing.

• A total of 4 advertising campaigns were run over this period. There were two sets of ad copy (set 1 and set 2) and both were run on two search engine sites (AAA and BBB). The resulting campaign values are:

  • AAA-1
  • AAA-2
  • BBB-1
  • BBB-2

  Lets find all the emails of all users who received a campaign on website BBB.

• Find all the emails of all users who received ad copy 2 in their campaign.

• Find the emails for all users who received both a campaign and a test. These users will have non-empty entries in the campaign and test columns.

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08. Davie’s Burgers Subway Ad

Project Goals

‘Davie’s Burgers’ the restaurant business has been booming and it is now looking to place a catchy advertisement in the local subway station. Lets help them dig into their orders table to see if there is anything interesting in there for a funny tagline!

• How recent is this data?
• The special_instructions column stores the data where Davie’s Burgers customers leave a note for the kitchen or the delivery. Lets see the result to 20 rows.
• Let’s search for special instructions that have the word ‘sauce’. Are there any funny or interesting ones?
• Let’s search for special instructions that have the word ‘door’. Any funny or interesting ones?
• Let’s search for special instructions that have the word ‘box’. Any funny or interesting ones?
• Some of these are marketing gold! But what are their order numbers?

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